Flow

Launch the Langflow visual workflow builder with PraisonAI Agent + AgentTeam components pre-loaded

The praisonai flow command launches Langflow with PraisonAI components pre-loaded, and provides YAML ↔ Langflow JSON conversion utilities.

Quick Start

1. Install

   pip install "praisonai[flow]"
   
2. Launch

   praisonai flow
   
3. Build visually

   Open http://localhost:7860 and drag Agent / Agent Team components from the PraisonAI sidebar.

---

How It Works

Phase	Description
Install	pip install "praisonai[flow]" pulls Langflow and requests
Launch	CLI sets LANGFLOW_COMPONENTS_PATH to PraisonAI components
Build	Drag Agent and Agent Team nodes in the browser
Export	praisonai flow export <flow_id> converts back to YAML

---

Subcommands

praisonai flow

Start the visual builder.

Flag	Type	Default	Description
--port, -p	int	7860	Port to listen on
--host, -H	str	127.0.0.1	Host to bind to (use 0.0.0.0 to expose)
--env-file	str	None	Path to a .env file Langflow should load
--no-open	flag	False	Don’t open the browser on start
--log-level, -l	str	error	debug, info, warning, error, critical
--backend-only	flag	False	Run backend API only (no frontend UI)
--components-path	str	None	Extra custom components directory (appended to PraisonAI’s)

praisonai flow --host 0.0.0.0 --port 8080

praisonai flow import

Convert PraisonAI YAML → Langflow JSON and upload.

Flag	Type	Default	Description
yaml_path	str	—	Path to YAML workflow file (positional)
--url	str	http://localhost:7860	Langflow server URL
--dry-run	flag	False	Preview JSON without uploading
--open	flag	False	Open the imported flow in the browser
--output, -o	str	None	Save JSON to file instead of uploading

praisonai flow import my_workflow.yaml --open

praisonai flow export

Download a Langflow flow and convert back to YAML or JSON.

Flag	Type	Default	Description
flow_id	str	—	Flow ID to export (positional)
--output, -o	str	<flow_name>.<ext>	Output file path
--url	str	http://localhost:7860	Langflow server URL
--format	str	yaml	Output format: yaml or json

praisonai flow export abc-123-def -o my_workflow.yaml

praisonai flow list

List flows on a running Langflow server.

Flag	Type	Default	Description
--url	str	http://localhost:7860	Langflow server URL
--search, -s	str	None	Search flows by name or description

praisonai flow list --search research

praisonai flow version

Show installed Langflow version.

praisonai flow version

---

Common Patterns

# YAML → visual editor round-trip
praisonai flow                                   # 1. start the builder
praisonai flow import my_workflow.yaml --open    # 2. push YAML in
# (edit in browser, copy the flow ID from the URL)
praisonai flow export <flow_id> -o my_workflow.yaml   # 3. pull edits back to YAML

# Preview the converted JSON without uploading
praisonai flow import my_workflow.yaml --dry-run

# Run on a custom port / expose to LAN
praisonai flow --host 0.0.0.0 --port 8080

# Headless / API-only deploy
praisonai flow --backend-only --no-open

---

Best Practices

Keep YAML as source of truth

Always export back to YAML for version control after visual edits.

Use --dry-run before uploading

Preview JSON conversion with praisonai flow import workflow.yaml --dry-run before pushing to a running server.

Add custom components with --components-path

Extend the sidebar with your own Langflow components via --components-path /path/to/components.

Run --backend-only for headless deployments

Skip the UI in CI or Docker with praisonai flow --backend-only --no-open.

---

Related

Visual Workflow Builder

UI guide for Agent and Agent Team nodes

Langflow Integration

Component reference and model formats

Dashboard

Unified dashboard — launches Flow + Claw + UI together

Installation Extras

[flow] extra reference